| --- |
| title: Python Dependency Compatibility Board |
| emoji: 🐍 |
| colorFrom: blue |
| colorTo: purple |
| sdk: gradio |
| sdk_version: 4.0.0 |
| app_file: app.py |
| pinned: false |
| license: mit |
| --- |
| |
| # 🐍 Python Dependency Compatibility Board |
|
|
| A powerful tool to analyze and resolve Python package dependencies. Check for version conflicts, compatibility issues, and generate clean `requirements.txt` files. |
|
|
| ## ✨ Features |
|
|
| - **Multiple Input Methods**: Library list, requirements.txt paste, or file upload |
| - **Conflict Detection**: Automatically detects version conflicts and compatibility issues |
| - **🤖 AI-Powered Explanations**: Uses LLM to generate intelligent, natural language explanations for conflicts (with fallback to rule-based) |
| - **Dependency Resolution**: Uses pip's resolver to find compatible versions |
| - **Environment Aware**: Configure Python version, device (CPU/GPU), and OS |
| - **Analysis Modes**: Quick (top-level) or Deep (with transitive dependencies) |
| - **Resolution Strategies**: Latest compatible, stable/pinned, keep existing, or minimal changes |
| - **Spell Checking**: Auto-corrects common spelling mistakes in package names |
| - **Validation Utilities**: Benchmark against the bundled synthetic dataset and generate perturbed requirements for stress testing |
|
|
| ## 🚀 How to Use |
|
|
| ### Input Your Dependencies |
|
|
| You can provide dependencies in three ways: |
|
|
| 1. **Library List**: Enter package names one per line |
| ``` |
| pandas |
| torch |
| langchain |
| fastapi |
| ``` |
|
|
| 2. **Requirements Text**: Paste your existing requirements.txt |
| ``` |
| pandas==2.0.3 |
| torch>=2.0.0 |
| langchain==0.1.0 |
| ``` |
|
|
| 3. **File Upload**: Upload a requirements.txt file directly |
|
|
| ### Configure Environment |
|
|
| - **Python Version**: Select your target Python version (3.8-3.12) |
| - **Device**: CPU only, NVIDIA GPU (CUDA), Apple Silicon (MPS), or Custom |
| - **Operating System**: Any, Linux, Windows, or macOS |
|
|
| ### Analysis & Resolution |
|
|
| 1. Choose **Analysis Mode**: |
| - **Quick**: Fast analysis of top-level dependencies |
| - **Deep**: Complete dependency tree with transitive dependencies |
|
|
| 2. Select **Resolution Strategy**: |
| - **latest_compatible**: Resolve to latest compatible versions |
| - **stable/pinned**: Prefer stable, pinned versions |
| - **keep_existing_pins**: Preserve your existing version pins |
| - **minimal_changes**: Make minimal changes to resolve conflicts |
|
|
| 3. Click **"Analyze & Resolve Dependencies"** |
|
|
| 4. Review the results and download your resolved `requirements.txt` |
|
|
| ## 🔍 What It Detects |
|
|
| The tool automatically detects: |
|
|
| - **Duplicate Packages**: Same package specified multiple times with conflicting versions |
| - **PyTorch Compatibility**: Ensures pytorch-lightning>=2.0 works with torch>=2.0 |
| - **FastAPI/Pydantic**: Checks version compatibility (e.g., fastapi 0.78.x requires pydantic v1) |
| - **TensorFlow/Keras**: Validates TensorFlow/Keras version pairs |
| - **Version Conflicts**: Identifies incompatible version specifications |
|
|
| ## 🤖 AI Explanations |
|
|
| When enabled, the tool uses LLM reasoning to provide: |
| - **Clear Explanations**: Natural language descriptions of what the conflict is |
| - **Why It Happens**: Technical reasons behind the conflict |
| - **How to Fix**: Actionable solutions with specific version recommendations |
|
|
| The LLM explanations use Hugging Face Inference API (free tier) and automatically fall back to rule-based explanations if the API is unavailable. |
|
|
| ## 📋 Example |
|
|
| **Input:** |
| ``` |
| torch==1.8.0 |
| pytorch-lightning==2.2.0 |
| pandas==2.0.3 |
| ``` |
|
|
| **Output:** |
| ``` |
| ⚠️ Compatibility Issues Found: |
| - pytorch-lightning>=2.0 requires torch>=2.0, but torch<2.0 is specified |
| |
| Resolved requirements.txt: |
| torch==2.1.0 |
| pytorch-lightning==2.2.0 |
| pandas==2.0.3 |
| ... |
| ``` |
|
|
| ## 🛠️ Technical Details |
|
|
| - Built with [Gradio](https://gradio.app/) |
| - Uses `packaging` library for version parsing |
| - Leverages pip's dependency resolver |
| - Supports PEP 508 requirement specifications |
|
|
| ## 📝 Notes |
|
|
| - Full dependency resolution requires pip >= 22.2 |
| - Deep mode may take longer for large dependency sets |
| - The tool works best with packages available on PyPI |
| - Platform-specific dependencies (e.g., CUDA) are detected but resolution may vary |
| - Run `python validation_tools.py` to benchmark the built-in compatibility checks against synthetic cases. |
| - Use `python scripts/perturb_requirements.py --help` to generate noisy/invalid requirements for robustness testing. |
|
|
| ## 🤝 Contributing |
|
|
| Feel free to test the tool and report any issues! This tool is designed to help developers manage Python dependencies more effectively. |
|
|
| ## 📄 License |
|
|
| MIT License - feel free to use and modify as needed. |
|
|
| --- |
|
|
| **Made with ❤️ for the Python community** |
|
|
